Fuelling the Data-driven Approach to Business - Data Lifecycle Management
Fuelling the Data-driven Approach to Business - Data Lifecycle Management

What is Data Lifecycle Management?

Data Lifecycle Management (DLM) describes the steps, processes, and policies followed by an organisation to manage the influx of business data throughout its life. It is a comprehensive approach rather than a single, specific product. The flow of information is managed across various systems, databases, applications, and storage media.

DLM helps organisations understand inventories and control their data through creation, modification, storage, and deletion. This enables organisations to have the most useful and recent records at their disposal with ease and efficiency. It also helps determine at what stage information should be deleted. DLM can be automated into repeatable steps to enable simpler ways to prioritise information.

Unlike Information Lifecycle Management (ILM), which focuses on nuances of the data files, what it contains, and how relevant or accurate it is, DLM focuses on entire files. DLM suggests that record files become more and more obsolete with each passing lifecycle stage. Thus, speed and accessibility for stale data are no longer considered necessary.

An efficient DLM process helps structure and organise a business’ data, thereby ensuring data security and availability.

Challenges Faced by an Organisation When DLM is Not Implemented Properly

As businesses move towards an increasingly digital and data-driven environment, it is crucial to have a good DLM process in place. In the absence of proper implementation of DLM, organisations can face challenges such as:

  • Mobile and web applications generate huge amounts of data from multiple sources. Managing this rapid expansion of unstructured data without a good DLM strategy can vastly increase storage costs.
  • Without proper data processing, organisations are at risk of a data security breach, leading to disruptions in the workflow.
  • In the absence of data security and data privacy regulations, more and more organisations are at the risk of being penalised on the grounds of non-compliance.
  • In the absence of DLM, organisations find it tough to respond to electronic discovery demands, leading to delays promptly.
  • Without leveraging strategic data value via business intelligence tools and analytics, organisations could potentially miss out on several growth opportunities.

Major Application of DLM in Organisations

As businesses move towards an increasingly digital and data-driven environment, it is crucial to have a good DLM process in place. In the absence of proper implementation of DLM, organisations can face challenges such as:

  • Insufficient resource:
    Keeping every bit of relevant data organised helps business processes use it easily while also protecting it from privacy breaches.
  • Data storage management:
    Data needs to be stored optimally with all the necessary security controls in place, following both internal policies and external data privacy compliance regulations. This necessitates detailed data management reporting.
  • Data usage and role-based security:
    Whenever data is discovered, edited, copied, detached, extracted, retrieved, archived, or modified, it needs to be instantly classified and reported.
  • Data sharing:
    Data should be discoverable by all employees across all public and private storage locations, with appropriate communication regarding the nature of their sensitivity so that employees can take proper privacy action.
  • Efficient archival:
    Archived data needs to be available and precisely classified, following all necessary compliance rules and guidelines.
  • Data removal:
    Deletion of data needs to be done carefully, following appropriate disposal methods as mandated by local or international laws.

5 Major Steps Involved in Managing Vast Amounts of Data

From creation to destruction, a data lifecycle goes through five major phases, which are:

PHASE 1 – Data Creation

The first phase involves the creation, acquisition, entry, or capturing of data. This could be in any form, like SQL database, images, videos, PDFs, etc.

PHASE 2 – Storage

After data is captured, the next step is to store and protect it so that it remains secure. Retention of data is generally ensured using a reliable backup and recovery process.

PHASE 3 – Usage

The third step is to make use of the stored data by the organisation to support its various activities. The organisation can view, process, modify, and save data and also share it externally.

PHASE 4 – Archival

Archiving data enables organisations to extract old data copied into its environment in case it is needed again for active production. An archive is a storage place for data without any maintenance or usage.

PHASE 5 – Destruction

Storing and archiving every fragment of data ever created is not a feasible option due to the enormity of data accumulated over time. Data destruction involves the removal or deletion of data that is no longer needed.

DLM and its Best Practices in Enterprises

Some of the best DLM practices for enterprises are:

  • Classify your data into different categories and define it as public, sensitive, internal, or restricted. This makes it easier to establish guidelines surrounding the sensitivity of the information and its value to an organisation.
  • Have a data recovery plan in place. Archiving data early and often is important to account for errors so that copies of data records are available at an organisation’s disposal whenever needed.
  • Every stakeholder in the organisation should communicate a comprehensive data management policy that can be implemented in a timely manner. A clear DLM policy helps streamline an organisation’s goals, with everyone being on the same page.
  • Lastly, follow a strict compliance policy, covering industry standards, government policies, and state regulations. These guidelines should also be revisited yearly to keep yourself updated with industry changes.

5 Major Benefits of DLM

A good data lifecycle management has several advantages for a business’s day-to-day operations:


It can cut down costs by moving data that is no longer needed to cheaper on-premise storage locations or in the cloud. DLM reduces costs for data backup, replication, and archiving by using optimal solutions.

Data Governance and Compliance

DLM helps organisations efficiently follow compliance standards, government regulations, and other rules related to legal, investigations, privacy, and auditing.

Protection of Data

Data security is a top priority for organisations in today’s digital era. DLM helps with data protection by preventing data loss, deletion, cyberattacks, etc. This helps prevent data breaches and misuse of critical information.

Better Workflow

DLM helps maintain the quality of data throughout its lifecycle, which helps improve organisational efficiency and workflow processes. It ensures that data is accurate and reliable, and thereby maximises data value.

Easier Data Accessibility

DLM develops strategies to tag metadata consistently so that it is easily accessible whenever needed. The easy and quick availability of valuable data improves business processes.

Final Thoughts on DLM

Data Lifecycle Management can seem like a vast and daunting topic to tackle. But its importance for organisations in today’s digital age is undeniable. Let’s look at a few key takeaways:

  • Once a business grows to a particular size, it is crucial to implement a good data lifecycle management strategy to ensure smooth workflow processes.
  • DLM ensures accessibility, accuracy, and security of data, while also taking care of various data compliance measures and guidelines.
  • The next step to DLM is Information Lifecycle Management (ILM), which can help organisations gain deeper insights and control over their data usage.

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